tailieunhanh - Báo cáo khoa học: "Dependencies between Student State and Speech Recognition Problems in Spoken Tutoring Dialogues"

Speech recognition problems are a reality in current spoken dialogue systems. In order to better understand these phenomena, we study dependencies between speech recognition problems and several higher level dialogue factors that define our notion of student state: frustration/anger, certainty and correctness. We apply Chi Square (χ2) analysis to a corpus of speech-based computer tutoring dialogues to discover these dependencies both within and across turns. | Dependencies between Student State and Speech Recognition Problems in Spoken Tutoring Dialogues Mihai Rotaru University of Pittsburgh Pittsburgh USA mrotaru@ Diane J. Litman University of Pittsburgh Pittsburgh USA litman@ Abstract Speech recognition problems are a reality in current spoken dialogue systems. In order to better understand these phenomena we study dependencies between speech recognition problems and several higher level dialogue factors that define our notion of student state frustra-tion anger certainty and correctness. We apply Chi Square x2 analysis to a corpus of speech-based computer tutoring dialogues to discover these dependencies both within and across turns. Significant dependencies are combined to produce interesting insights regarding speech recognition problems and to propose new strategies for handling these problems. We also find that tutoring as a new domain for speech applications exhibits interesting tradeoffs and new factors to consider for spoken dialogue design. 1 Introduction Designing a spoken dialogue system involves many non-trivial decisions. One factor that the designer has to take into account is the presence of speech recognition problems SRP . Previous work Walker et al. 2000 has shown that the number of SRP is negatively correlated with overall user satisfaction. Given the negative impact of SRP there has been a lot of work in trying to understand this phenomenon and its implications for building dialogue systems. Most of the previous work has focused on lower level details of SRP identifying components responsible for SRP acoustic model language model search algorithm Chase 1997 or prosodic characterization of SRP Hirschberg et al. 2004 . We extend previous work by analyzing the relationship between SRP and higher level dialogue factors. Recent work has shown that dialogue design can benefit from several higher level dialogue factors dialogue acts Frampton and Lemon 2005 Walker et al. 2001 pragmatic

• Báo cáo khoa học
• Dependencies between Student State
• Speech Recognition Problems
• Spoken Tutoring Dialogues
• báo cáo khoa học
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Bài giảng Xử lý ngôn ngữ tự nhiên
• Ngôn ngữ tự nhiên
• Kỹ thuật lập trình
• Xử lý nhập nhằng ngữ nghĩa
• Xử lý ngữ nghĩa
• Xử lý ngôn ngữ
• Natural Language Processing
• Ngôn ngữ lập trình
• Nhập nhằng cấu trúc
• Tri thức về ngôn ngữ
• Mô hình n gram
• Dịch máy
• Phương pháp dịch máy
• Hiểu ngôn ngữ
• Phân tích ngữ nghĩa
• Phân loại tin tự động
• Biểu diễn vị từ
• Thuộc tính về sự kiện
• Thuộc tính về sự kiện
• Mô hình ngôn ngữ Google Book N grams
• Mô hình ngôn ngữ KenLM
• Phương pháp làm mịn
• Tách từ tiếng Việt
• Gán nhãn từ loại
• Phân tích cú pháp
• Nghĩa từ vựng
• Phân giải nhập nhằng từ
• Phân loại văn bản
• Lexical chain
• Phản hồi thông tin
• Bài toán PTCP
• Cấu trúc ngữ pháp
• Phân tích cú pháp xác suất
• CKY kết hợp xác suất
• Văn phạm phi ngữ cảnh xác suất
• Hình thái học